School of CSE - Details Needed for New Course Proposal

Course Title: Knowledge Representation and Reasoning

Rationale
Why is the new course being proposed?

Knowledge Representation and Reasoning (KRR) is at the core of Artificial
Intelligence. All facets of AI make use of KRR to some extent or other.
With the presence of NICTA and its Knowledge Representation and
Reasoning Program we have a large body of expertise in this area.
Further NICTA Level E appointments in the area of constraint programming
will further bolster our expertise and resources.
Existing courses on AI cover KRR on a very basic level, by mainly
introducing propositional and first-order logic and by presenting some
historical KRR concepts like rules, semantic nets and frames.
We want to give students an advanced and more up-to-date introduction to
KRR. This covers mainly recent trends and current research issues
with which our group has expertise.

What are the academic objectives?

Introduce students to current research issues in KRR and prepare them for
a thesis or project.

Which programs/stage does it serve?

BSc, BSE, BCE 4th year; MSc/PhD

Why can the same objectives not be achieved with existing courses?

Current AI courses cover KRR only as one of many topics and give only a
very basic introduction and historical overview.

How does the proposed course relate to other courses?

It is an extension of the AI courses COMP3411: Artificial Intelligence,
COMP9414: Artificial Intelligence and is directed towards students who are
interested in AI and who want to that want to specialise. It is related to
the courses COMP4415: Logical Foundations of Artificial Intelligence,
COMP9417: Machine Learning, COMP4411: Experimental Robotics,
COMP4416: Intelligent Agents and to some extent COMP9444: Neural Networks.
It complements them all quite nicely.

What overlap is there?

The AI courses COMP3411, COMP4415, COMP9414 give a basic introduction to
KRR. We build on that introduction and deal with more advanced topics.
In the first three hours we give a short summary of these basics, which is the
only overlap.

If there is any overlap, why is this justified/not a problem?

The overlap consists only of a short recap of what was done in the
introductory AI courses regarding KRR.

Stakeholders and Consultation

Who are the potential stakeholders, who was consulted about the
proposal (inside the School as well as outside), what was the
result of that consultation?

The main consultation was held with the Artificial Intelligence researchers
within the department.

Mike Bain

Alan Blair

Paul Compton

Achim Hoffman

Eric Martin

Bill Wilson

Claude Sammut

Arcot Sowmya

Ron van der Meyden

Enrolment Impacts

Likely enrolment (with justification), and impact on enrolments of
other courses.

We expect that a fourth to a third of the attendants of the three offered
AI courses attend this course, so this course should have the same size as
the introductury AI courses. It might impact other advanced AI courses
such as COMP9417 Machine Learning, COMP9441 Cryptography and Security,
COMP9444 Neural Networks, COMP9511 Human-Computer Interaction, COMP9517
Computer Vision, COMP9518 Pattern Recognition and Vision in that students
who want to attend further AI courses decide to take our course instead of
one of the others.

Justification of Prerequisites (or lack thereof)

Prerequisites:
At least 12CP in COMP3xxx courses or above including
one of the introductory AI courses COMP3411, COMP4415,
COMP9414

Any Courses this is Replacing, and Why?

None.

Delivery and Assessment

Handbook Entry

Knowledge Representation and Reasoning (KRR) is at the core of Artificial
Intelligence. It is concerned with the representation of knowledge
in symbolic form and the use of this knowledge for reasoning.
This course presents current trends and research issues in Knowledge
Representation and Reasoning (KRR).
It enables students interested in Artificial Intelligence to deepen their
knowledge in this important area and gives them a solid background for
doing their own work/research in this area. The topics covered in more detail
are AI Logics, Probablilistic Reasoning, Constraints, and Game Theory. We
require that participants have completed at least one introductory AI course
(COMP3411, COMP4415, COMP9414).